The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Deep learning is a subfield of machine learning built on artificial neural networks with multiple layers that automatically learn hierarchical representations of data, reducing the need for manual feature engineering. Architectures include convolutional neural networks for image and spatial data, recurrent neural networks and long short-term memory networks for sequential data, and transformer models, which now underpin most state-of-the-art natural language processing and increasingly computer vision systems. Training deep networks typically relies on large labeled datasets, backpropagation, and gradient-based optimization, along with regularization techniques and specialized hardware such as GPUs and TPUs. A notable 2026 shift in the field favors smaller, specialized models over ever-larger ones, prioritizing reliability, transparency, and efficient inference over raw parameter count. Deep learning drives advances in image recognition, speech processing, machine translation, medical image diagnosis, and generative models for text, images, and audio. As an open-access deep learning journal, IJACSA covers novel deep learning architectures and their evaluation across vision, language, and applied domains.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
The aerospace industry increasingly relies on predictive models for aerodynamic coefficients to enhance design, performance, and optimization. While traditional methods like Computational Fluid Dynamics (CFD) and wind tu…
Road traffic accidents are a significant public health issue, particularly in developing nations, where infrastructure and traffic monitoring systems may be limited. Risky situations including sudden stopping, lane switc…
Vehicle classification offers intelligent solutions for road traffic monitoring by enabling future prediction planning and decision making. Predictive analytics can be used to predict traffic congestion based on the type…
Stroke continues to be a major cause of mortality and disability globally, and precise risk prediction models are needed. Current models do not effectively incorporate temporal patient information, restricting the qualit…
Traditional green view rate (GVR) methods, which rely on two-dimensional planar images, have several limitations. They fail to capture the three-dimensional spatial characteristics of urban greenery, are frequently depen…
With the continuous development of information technology, public opinion analysis based on open-source texts and financial situation awareness has become a research hotspot. This study focuses on financial news and comm…
Radio Frequency Identification is a fast and reliable communication module that performs automatic data capture to identify and track individual objects and people. Frequency-coded tags employ resonant networks to decode…
In resource-limited settings, assisting physicians with disease identification can significantly improve patient outcomes. Early diagnosis is crucial, as many patients could remain healthy with timely intervention. Recen…
Down syndrome is a genetic disorder caused by the presence of an extra copy of chromosome 21, affecting both neurological development and physical features. Early and accurate diagnosis is critical for ensuring timely me…
Automated recognition of sign languages has been playing an important role in breaking barriers to communication and inclusion for the deaf and mute community. Several studies have been conducted on Bengali Sign Language…
